1. Field of the Invention
This invention relates to a method and system for generating pattern information on a specific figure into a bit pattern, and further relates to a pattern defect inspection method and system employing the preceding method and system for inspecting photomasks or reticles for pattern defects such as pattern disconnections in the manufacture of semiconductor integrated circuit elements.
2. Description of the Related Art
In the manufacture of semiconductor integrated circuit elements, pattern defects such as pattern disconnections in the photomask used for pattern transfer produce no desired elements, resulting in a reduction in the fabrication yield.
Conventionally, photomasks produced by an electron beam exposure system have been inspected with a mask defect inspection system. As shown in FIG. 1, with the inspection apparatus, rays of light generated at a lamp 101 are illuminated onto a photomask 110. A photodiode array 102 then detects an optical signal corresponding to the pattern formed on the mask 110. A data comparator circuit 103 compares and collates a reference signal based on the design data on the formation of the design pattern on the mask 110 with the optical signal detected at the photodiode array 102. Based on the results, it is possible to decide whether of not pattern defects exist on the mask 110 and make a yes-no decision about the pattern being inspected.
The operation of such a mask defect inspection apparatus will now be described.
The apparatus generally performs unit frame inspection, in which a pattern is inspected by moving the table 104 continuously in the X or Y direction each time the table 104 moves by the frame width in the direction perpendicular to that of the continuous movement. The unit frame inspection covers the entire pattern-forming surface area on the photomask 110.
The photodiode array 102 and a sensor circuit 105 detects an optical signal corresponding to the actual pattern on the photomask 110, and then supplies it to the data comparator circuit 103. At the same time, a bit pattern generator 107 reads from a computer 106 design data used to form a design pattern on the photomask 110, and based on the signal from a bit pattern generator 107, produces a reference signal. It then compares and collates the optical signal and the reference signal for each measuring position on the table 104. The comparing and collating processes are performed with the table 104 in continuous motion at a constant speed.
Here is a concrete example of a defect judging method, which has been employed by the above-mentioned mask defect inspection apparatus to judge whether or not defects exist by comparing the optical signal based on actual pattern detection with the reference signal based on the design pattern.
Using information P (x, y) on the design pattern (letter F, in this case) as shown in (A) of FIG. 2 and the sensitivity characteristics F (x, y) for the photodiode 102 as shown in (B) of FIG. 2, the predicted sensor output (optical signal) R, as shown in (C) of FIG. 2, for the image-forming system is calculated. The data comparator circuit 103 then compares the actual output S of the sensor 105 as in (D) of FIG. 2 (here, the output at the position 3.times.3 in the top right corner reads a small value "3") with the predicted sensor output R of (C) of FIG. 2, and when the resulting difference is larger than a preset signal level, judges that there is a defect at the position corresponding to the judged data. For FIGS. 2(A) through (D) the output difference between the defective portion and the design data is 2 (=5-3). In this case, a signal level difference equal to or more than 1 is previously defined as defective. Consequently, the output difference of 2 is judged to be defective.
In such a comparing method, however, the area dimension for a piece of data on the predicted sensor output R (bit dimension in the design data) fails to agree completely with a single area dimension for the actual sensor output S (a single pixel dimension in the actual measurement data). Specifically, when the area dimension for the actual sensor output S is 0.6 [.mu.m], the corresponding area dimension for the design data is 0.5 [.mu.m]. Here, an area dimension is defined as an area (size) specified by a piece of data.
The cause of the bit dimension in the design data disagreeing with a single pixel dimension in the actually measured data will now be discussed. Of several known causes, two typical ones will be taken up here. Referring to FIG. 3, the first cause will be explained. Since a figure (a pattern) is defined in dots based on the patterning data supplied from the electron beam patterning apparatus instead of being defined in actual dimensions, the bit dimension in the design data fails to coincide completely with a single pixel dimension from the sensor. For instance, as shown in FIG. 3, to obtain an actual pattern with a 256 [.mu.m] width (a256 [.mu.m] deflecting width), it is necessary to draw a single bit using a beam with a1 [.mu.m/spot] size obtaining an actual pattern with a128 [.mu.m] width (a128 [.mu.m] deflecting width) requires a0.5 [.mu.m/spot] size beam per bit; and achieving an actual pattern with a64 [.mu.m] (a64 [.mu.m] deflecting width) width needs a0.25 [.mu.m/spot] size beam per bit. The reason why the patterning beam spot size can be set to only discrete values is that the beam spot size depends on the deflection width in the electron beam exposure apparatus. That is, changing the deflection width of the exposure apparatus according to each of the patterning areas 256 [.mu.m], 128 [.mu.m], and 64 [.mu.m], allows the patterning beam width to assume values stepwise. Thus, it is impossible that the bit dimension in the design data agrees completely with a single pixel dimension from the sensor. It is apparent that the limited setting of the patterning beam width to specified values prevents the dimension R (the predicted sensor output) based on the design data from perfectly coinciding with the actual pixel dimension (the sensor output).
The mask is drawn by a technique known as scaling. In this technique, the dimensions obtained from the design data is varied by multiplying them by a scaling factor that assumes different values. The change of dimension can be achieved by narrowing or broadening the deflecting width and the beam spot size. A different pattern is drawn based on the same data by varying the deflection width of the electron beam according to the scaling. In the scaling technique, the beam width per actual bit is varied by multiplying the dimension obtained from the design data by one of different magnifications available. A similar problem arises that the dimension per dot and the sensor pixel dimension do not coincide, preventing improvements in the defect detecting level.
The second cause of the bit dimension in the design data disagreeing with a single pixel dimension in the sensor will now be explained. In an ordinary inspection apparatus, inspection is often carried out with two modes of measurement accuracy: rough mode and precision mode. Usually, the mode remains unchanged for the same substrate. The change of measurement accuracy is achieved by changing optical characteristics. A concrete example of changing optical characteristics is the change of magnification of an object lens. Because of the difficulty in changing a magnification in steps of an integral multiple, the magnification is an integral multiple containing errors. The errors in the magnification cause the sensor pixel dimension to make optical minute fluctuations, resulting in a disagreement problem between the bit dimension in the design data and a single pixel dimension in the sensor.
When a bit dimension in the design data disagrees with a single pixel dimension in the sensor as mentioned above, the process shown in FIG. 4 is done in practice. Here, the comparison data (R) is formed by curtailing the design data. Defects are detected by comparing the comparison data (R) with the actual measurement data (S). This comparing process includes processes shown in FIGS. 2A through 2D. To be exact, however, there are some local positional differences between the design data and the actual measurement data. Thus, the comparison inspection is performed in the situation involving such differences. For instance, if the actual measurement data is given in units of 0.6 [.mu.m] and the design data in units of 0.5 [.mu.m], comparison is carried out at the correct positions at regular intervals of 3 [.mu.m] that is the least common multiple of 0.6 [.mu.m] and 0.5 [.mu.m]. At other positions, however, positional differences of up to -0.3 [.mu.m] appear. For instance, when m=3 and n=3, the following equation is given: EQU 0.5.times.m-0.6.times.n=-0.3
To minimize such a positional difference, after a piece of data for m=4 is discarded, data for m=5 and n=4 are compared. However, the positional difference thus minimized varies with the scaling factor in the electron beam patterning apparatus.
With the presence of positional differences, comparison of the predicted sensor output (design data) R calculated with the sensor output (actual measurement data) causes many spurious defects to be detected. Detection of such spurious defects makes impossible highly accurate detection of real defects.
More detailed descriptions will be given for the case of curtailing data as described above, referring to FIG. 5, and for the case of performing the process opposite to the data curtailment, referring to FIG. 6. In the data curtailment of FIG. 5, although the sensor output has a defect at a specific position, the defect cannot be detected because the design data happens to have the corresponding data curtailed. Contrarily, in FIG. 6, a specific position (bit) in the design data is referred to repeatedly instead of curtailing data from the design data. In both cases, despite the absence of defects in the sensor output, a specific position (bit) in the sensor output has no corresponding position in the design data being compared, leading to the judgment that there is a defect at the position.
The spurious defect problem in the inspection process of semiconductor elements is related to a problem with the manufacturing process of semiconductor elements. Thus, the disagreement of actual measurement data with design data can be discussed in the same manner as the disagreement of design data with actual measurement data. Consequently, improving the bit pattern generation technique used in the manufacturing processes of semiconductor elements leads to improvements in the pattern defect inspection technique used in the inspection process of semiconductor elements. The reverse is also true. That is, the minimization of spurious defects for higher inspection accuracy is achieved directly by improving the pattern defect inspection technique and indirectly by improving the bit pattern generatement technique.